Hello all, I have been attempting to generate ICC analyses for an imputed dataset by using the proc mixed statement detailed below: proc mixed data = e.imputepeappend; by _imputation_; class admin subid; model bpedqtot = admin; random int /sub= subid type = un; repeated/sub=subid type = sp(pow) (admin) rcorr = 1,2 local ; parms .56 .13 .5 .13; ods output CovParms = cov_estimates_pe; run; This appears to generate the results that my colleagues and I are looking for (the variance of bpedqtot across administration timepoints, i.e., admin), but I cannot properly aggregate the covariance parameters of all 50 imputations. I have been using this code, but I cannot seem to get it to run properly: proc mianalyze data = cov_estimates_pe ; where CovParm = "admin"; modeleffects CovParm subject estimate ; run; And I will receive the following error: ERROR: The input TYPE= data set is not a valid data set without specifying variables for standard errors in the STDERR statement. From what I understand, the main issue seems to be that I cannot generate results for the standard error, as the mixed model only produces "Cov Parm", "Subject", and "Estimate" values: (covariance table for imputation 1) Is there any way for me to properly run the proc mianalyze statement without having any standard error values? PS. Sorry if any of my terminology is off, I'm still somewhat inexperienced with SAS and programming in general.
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